Curated by Applysci.

AI

MIT’s Bob Langerand Giovanni Traversohave developed a 3D-printed, wirelessly-controlled, ingestible capsule that can deliver drugs, sense environmental conditions, or both. It can reside in the stomach for a month. Data is sent to a user’s phone, and...

Lawson Health Research Institute, Mind Research Network and Brainnetome Center researchers have developed an algorithm that analyzes brain scans to classify illness in patients with complex mood disorders and help predict their response to medication....

Google’s Lily Peng has developed an algorithm that can predict heart attacks and strokes by analyzing images of the retina. The system also shows which eye areas lead to successful predictions, which can provide...

Sergey Levine and UC Berkeley colleagues have developed robotic learning technology that enables robots to visualize how different behaviors will affect the world around them, with out human instruction. This ability to plan, in various scenarios,...

Andrew Ng and Stanford colleagues used AI to detect pneumonia from x-rays with similar accuracy to trained radiologists. The CheXNet model analyzed 112,200 frontal-view X-ray images of 30,805 unique patients released by the NIH...

Yuichi Mori and Showa University colleagues haved used AI to identify bowel cancer by analyzing colonoscopy derived polyps in less than a second. The system compares a magnified view of a colorectal polyp with 30,000...

MIT’s Regina Barzilay has used AI to improve breast cancer detection and diagnosis. Machine learning tools predict if a high-risk lesion identified on needle biopsy after a mammogram will upgrade to cancer at surgery, potentially...

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The conference is co-sponsored by the Stanford Wearable Electronics Initiative (e-WEAR). Become an affiliate member of e-WEAR and learn more about Stanford activities on wearable electronics. The e-WEAR annual affiliate member meeting will precede the conference. http://wearable.stanford.edu